Method of operating an automated radiopharmaceutical synthesizer

ABSTRACT

The present invention relates to calibration and normalization systems and methods for ensuring the quality of radiopharmaceuticals during the synthesis thereof, such as radiopharmaceuticals used in Positron Emission Tomography (PET) and Single-Photon Emission Computed Tomography (SPECT).

CROSS-REFERENCE

This patent claims the benefit of priority to U.S. patent applicationSer. No. 14/348,690, filed on Mar. 31, 2014, entitled “Method OfOperating An Automated Radiopharmaceutical Synthesizer,” which claimsthe benefit of priority to PCT Patent Application No. PCT/US2012/056868,filed on Sep. 24, 2012, entitled “Method Of Operating An AutomatedRadiopharmaceutical Synthesizer,”, which claims the benefit of priorityto U.S. Provisional Patent Application No. 61/541,296, filed on Sep. 30,2011, entitled “Calibration and Normalization Systems and Methods forRadiopharmaceutical Synthesizers”, each of which is incorporated hereinby reference in its entirety for all purposes.

FIELD OF THE INVENTION

The present invention relates to calibration and normalization systemsand methods for ensuring the quality of radiopharmaceuticals during thesynthesis thereof, such as radiopharmaceuticals used in PositronEmission Tomography (PET) and Single-Photon Emission Computed Tomography(SPECT).

BACKGROUND

PET and SPECT imaging systems are increasingly used for detection ofdiseases and are useful in providing early detection and a definitediagnosis for such diseases (e.g., disease states within oncology andneurology). For example, currently, a large percentage of PET and SPECTtests are related to cancer detection and early Alzheimer detection.These diseases require early diagnosis to allow a timely and effectivetreatment.

PET and SPECT imaging systems create images based on the distribution ofpositron-emitting isotopes and gamma emitting isotopes, respectively, inthe tissue of a patient. The isotopes are typically administered to apatient by injection of radiopharmaceuticals including a probe moleculehaving a positron-emitting isotope, e.g., carbon-11, nitrogen-13,oxygen-15, or fluorine-18, or a gamma radiation emitting isotope, e.g.technetium-99. The radiopharmaceutical is readily metabolized, localizedin the body or chemically binds to receptor sites within the body. Oncethe radiopharmaceutical localizes at the desired site (e.g., chemicallybinds to receptor sites), a PET or SPECT image is generated.

Examples of known radiopharmaceuticals include ¹⁸F-FLT([¹⁸F]fluorothymidine), ¹⁸F-FDDNP(2-(1-{6-[(2-[¹⁸F]fluoroethyl)(methyl)amino]2-naphthyl}ethylidene)malonitrile),¹⁸F-FHBG (9-[4-[¹⁸F]fluoro-3-(hydroxymethyl)butyl]guanine or[¹⁸F]-penciclovir), ¹⁸F-FESP ([¹⁸F]-fluoroethylspiperone), ¹⁸F-p-MPPF(4-(2-methoxyphenyl)-1-[2-(N-2-pyridinyl)-p-[18p]fluorobenzamido]ethylpiperazine)and ¹⁸F-FDG ([¹⁸F]-2-deoxy-2-fluoro-D-glucose). Radioactive isotopes inradiopharmaceuticals are isotopes exhibiting radioactive decay, forexample, emitting positrons. Such isotopes are typically referred to asradioisotopes or radionuclides. Exemplary radioisotopes include ¹⁸F,¹²⁴I, ¹¹C, ¹³N and ¹⁵O, which have half-lives of 110 minutes, 4.2 days,20 minutes, 10 minutes, and 2 minutes, respectively.

Because radioisotopes have such short half-lives, the synthesis andpurification of the corresponding radiopharmaceutical must be rapid andefficient. Any quality control (QC) assessments on theradiopharmaceutical must also take place in a short period of time.

Preferably, these processes (i.e., synthesis, purification, and QCassessment) should be completed in a time well under the half-life ofthe radioisotope in the radiopharmaceutical. Presently, QC assessments(e.g., chemical yield and chemical purity) may be relatively slow mainlydue to the fact that they are conducted manually. Accordingly, there isa need for systems, components, and methods for capturing, analyzing,and interpreting data obtained during the synthesis and purificationprocesses of a radiopharmaceutical to ensure that those synthesis andpurification are proceeding efficiently to produce qualityradiopharmaceuticals in a desired quantity. From this analysis, changescan be implemented before, during or after the synthesis and/orpurification of the radiopharmaceutical to correct any deficiencies, asthey occur during the radiopharmaceutical's synthesis. The embodimentsof the present invention provide such systems, components, and methods,which allow for capture and analysis of real data, as well as thecorrection of deficiencies, during the synthesis of theradiopharmaceutical. A site to site comparison can also be performed toenable comparison across geographically diverse sites conductingradiopharmaceutical synthesis.

SUMMARY

An exemplary embodiment includes a method of monitoring aradiopharmaceutical synthesis process. Data relating to theradiopharmaceutical synthesis process is received from aradiopharmaceutical synthesizer. The data is analyzed. One or morecharacteristics of the data is identified wherein the one or morecharacteristics pertain to quality control factors relating to theradiopharmaceutical synthesis process. The one or more characteristicsof the data are extracted. The extracted data is analyzed.

Another exemplary embodiment includes a method of normalizing aradiopharmaceutical process. A first set of data relating to a firstradiopharmaceutical process is received from a first radiopharmaceuticalsynthesizer, wherein the first set of data is based on results using aknown input sample and includes data pertaining to the output of thefirst radiopharmaceutical process. A first correlation factor to beapplied the first set of data to normalize the first set to a firstbaseline is calculated. A second set of data relating to a secondradiopharmaceutical process is received from a secondradiopharmaceutical synthesizer, wherein the second set of data is basedon results using the known input sample and includes data pertaining tothe output of the second radiopharmaceutical process. A secondcorrelation factor to be applied to the second set of data to normalizethe second set to a second baseline is calculated. A comparison of thefirst set and second set of data is performed. A third correlationfactor that normalizes the first and second set of data to a thirdbaseline based upon the comparison is calculated.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a method for producing and using a PET or SPECT imagingagent and extracting data collection file data according to an exemplaryembodiment of the invention.

FIG. 2A depicts an exemplary first portion of a data collection fileaccording to an exemplary embodiment of the invention.

FIG. 2B depicts an exemplary second portion of a data collection fileaccording to an exemplary embodiment of the invention.

FIG. 3 depicts a plot of data collection file data according to anexemplary embodiment.

FIG. 4 depicts a plot of data collection file data with an overlay ofsynthesizer components according to an exemplary embodiment.

FIG. 5 depicts a plot of data collection file data showing the yieldsteps according to an exemplary embodiment.

FIG. 6 depicts a set of yield predictions and reported yields accordingto an exemplary embodiment.

FIGS. 7A and 7B depict a section of a plot of data collection file dataaccording to an exemplary embodiment.

FIG. 8 depicts a section of a plot of a series of traces of datacollection file data during the final purification step according to anexemplary embodiment.

FIGS. 9A, 9B, and 9C depict traces of data collection file data fromdifferent synthesis sites according to an exemplary embodiment.

FIG. 10 depicts a data table corresponding to the traces of FIGS. 9A-Caccording to an exemplary embodiment.

These and other embodiments and advantages of the invention will becomeapparent from the following detailed description, taken in conjunctionwith the accompanying drawings, illustrating by way of example theprinciples of the various exemplary embodiments of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

It will be readily understood by those persons skilled in the art thatthe embodiments of the inventions described herein are capable of broadutility and application. Accordingly, while the invention is describedherein in detail in relation to the exemplary embodiments, it is to beunderstood that this disclosure is illustrative and exemplary ofembodiments and is made to provide an enabling disclosure of theexemplary embodiments. The disclosure is not intended to be construed tolimit the embodiments of the invention or otherwise to exclude any othersuch embodiments, adaptations, variations, modifications and equivalentarrangements.

The following descriptions are provided of different configurations andfeatures according to exemplary embodiments of the invention. Theseconfigurations and features may relate to providing systems and methodsfor quality control of radiopharmaceuticals and other compounds orformulations containing radioisotopes. While certain nomenclature andtypes of applications or hardware are described, other names andapplication or hardware usage is possible and the nomenclature providedis done so by way of non-limiting examples only. Further, whileparticular embodiments are described, these particular embodiments aremeant to be exemplary and non-limiting and it further should beappreciated that the features and functions of each embodiment may becombined in any combination as is within the capability of one ofordinary skill in the art.

The figures depict various functionality and features associated withexemplary embodiments. While a single illustrative block, sub-system,device, or component is shown, these illustrative blocks, sub-systems,devices, or components may be multiplied for various applications ordifferent application environments. In addition, the blocks,sub-systems, devices, or components may be further combined into aconsolidated unit. Further, while a particular structure or type ofblock, sub-system, device, or component is shown, this structure ismeant to be exemplary and non-limiting, as other structure may be ableto be substituted to perform the functions described.

Exemplary embodiments of the invention relate to synthesis systems forradiopharmaceuticals. The synthesis system may produceradiopharmaceuticals for use with either PET or SPECT scanners. Forexample, the synthesis system may be the FASTlab® system from GEHealthcare. The use of the FASTlab system in examples described hereinis meant to be exemplary and non-limiting. It should be appreciated thatthe embodiments described herein may be used with a variety of synthesissystems manufactured by companies other than GE Healthcare. It shouldfurther be appreciated that the use of the term “radiopharmaceutical”,“radiotracer”, “PET tracer”, or “SPECT tracer” herein is meant to beexemplary and non-limiting and the mention of one term does not excludesubstitution of the other terms in the described embodiment.

During the automated synthesis of radiopharmaceutical, a data collectionfile for the synthesis run is generally produced. For example, for everyradiopharmaceutical synthesis run on a FASTlab system, a unique log filefor the run is produced. This file consists of data collected at variouspoints in the synthesis using various sensors and activity detectorsthat are a part of the process, such as radioactivity detectors. Thedata in the data collection file may be collected at certain timeintervals. For example, in a FASTlab system, a log file consists of datacollected at one second intervals throughout the entire synthesis withthe data being measured by up to six different radioactivity detectors,as well as set values and measured values for the programmable processparameters in the FASTlab sequence file (e.g., reactor temperature,pressure, and syringe positions). It should be understood that the datacollection intervals may be adjusted and may be measured at differentintervals other than every second (e.g., every five seconds or every tenseconds). Data may be collected from different sensors or radioactivitydetectors at different intervals for each (e.g., every second at onedetector and every five seconds at another).

The data in the data collection file file, such as a log file, whenpresented graphically, represents a diagnostic “fingerprint” for anygiven FASTlab synthesis run. The fingerprint of a successful synthesisrun can be established based on established data. Subsequent synthesisruns may be then compared to the fingerprint of the successful synthesisrun in order to compare the performance of the synthesis system.Deficiencies or problem areas in the synthesis process can then beidentified and appropriate action taken. For example, deviations fromthe “good” or “acceptable” fingerprint can be determined and potentialproblem areas in the synthesis process can be identified, such as awhich step of the process is experiencing a problem or not performing upto expected standards. Using this technique, synthesizer processesacross multiple sites may also be compared. As part of such comparison,it may be necessary to calculate a correlation or normalization factor,as described below, to enable the data from each run to be moved to acommon baseline to ensure an accurate comparison between differentsynthesizers at different locations.

Accordingly, the data collection file can provide valuable informationabout each synthesis run and may be used, for example, to monitorvariations between identical runs; to see the effect of modifications tothe synthesis runs; for trouble shooting; and as a tool during PETcenter set-up. Useful information may therefore be obtained throughanalysis and correlation of the data collection file data. For example,quality control information, such as, for example, yield and purity, maybe extracted from the data collection file data and analyzed. Throughsuch analysis, the radiopharmaceutical synthesis process may be adjustedbased on this quality control information. This analysis process maysimplify quality control procedures through the potential elimination ofpost-production quality control tests since the results can bedetermined from the synthesis process itself.

In addition to the information from sensors and activity detectors, suchas the radioactivity detectors, the data collection file may contain setvalues and real, or measured, values for the programmable processparameters in the synthesizer's sequence file. For example, a FASTlablog file contains measurements of data from the following programmableprocess parameters: reactor heater temperature, nitrogen pressure,vacuum, and syringe position. Accordingly, the use of information fromthe activity detectors in combination with process parameters in thedata collection file adds valuable information regarding given steps andactions in the process.

According to other exemplary embodiments, using activity detectorreadings obtained from data collection files, the synthesizer reactionperformance may be monitored. However, radioactivity detectormeasurements need to be corrected and correlated in order to account forvariation in readings amongst different synthesizers located atdifferent locations or sites. In order to perform such a correction, acalibration or normalization process is used to standardize the processdata to enable comparison on an equivalent baseline. According to anexemplary embodiment, a basic sequence for the synthesizer is used wherea sample with a known amount of radioactivity is passed through thesynthesizer in the vicinity of the different radioactivity detectors. Acorrelation factor for each detector is then calculated based on theresults compared to the known radioactivity amount and used during thedata analysis to monitor the synthesizer process performance. Onceinstruments at different locations are calibrated or normalized, theresulting data can be collected and further normalized to account forvariations at the different locations. In doing so, data collected fromthe different locations can be meaningfully compared. This collecteddata can be centrally analyzed and stored in order to provide varioussupport functions to the different locations such as troubleshooting andcustomer service.

During the above process, the sample is passed throughout thesynthesizer hardware and the activity is read at each radioactivitydetector. During the process, when comparing two sites, say, sites A andB, each having a synthesizer, the data collection file may show that alldetectors in A read as expected, but one detector, for example, detector5 at B reads 10% below what is expected. If it is known that thedetector is functioning properly and is aligned properly, then thepresumption is that there is a systematic error associated with thatdetector that causes it to read low. The data is collected from sites Aand B at a central data collection site. The central collection sitewould use the data to normalize the data from the detectors at site Bupwards by 10% so that the data for the same detector at site A can becompared to the data from site B. Once calibrated, sites A and B proceedwith synthesis.

Each synthesizer typically generates a data collection file duringproduction of a radiopharmaceutical. The contents of the data collectionfile are transmitted to the same central data collection site either inreal time or at some point after the synthesis run is complete. Providedthe same radiopharmaceutical is being synthesized at each site, the datagenerated from sites A and B could be compared. The data for site B, ofcourse, would have to be normalized up to account for the fact that itsdetector 5, is known to read low. The data may show production trends orissues with each site. For example, the data collection file data couldshow that there was a good solid phase extraction (SPE) recovery, but alow reported yield in the synthesizer at site A. These data may thenform the basis for troubleshooting the synthesizer at site A. Uponanalysis of the data, a conclusion may be drawn with regard to theproblem at site A. For example, the conclusion could be that there was alow yield for the a radiolabelling step or some other synthesizer step.

The data collection file data may serve a number of uses. Exemplary,non-limiting uses may include:

Process development, including tuning of purification processes in asynthesizer, including the SPE process(es);

Robustness testing: a robust process would show little deviation fromrun to run since the graphical representation of the data for each ofthe radioactivity detectors are like “fingerprints” of the process;

Troubleshooting: problems can be spotted and pinpointed in theradiosynthesis from the trends of the radioactivity detectors deviatingfrom a successful production based on established data;

Support PET center set-up;

Ensuring production quantity matches the patient need (e.g., ensuringthat the proper number of patient doses is produced);

Identification of trends of the radioactivity detectors at various sitesto determine performance of different synthesizers;

Identification of synthesizer hardware problems;

Identification of synthesizer sequence file programming issue(s);

Simplified post-synthesis quality control;

Providing remote customer support; and

Normalization of data collection files, e.g., log files.

FIG. 1 depicts a flow chart of a method of synthesizing and using a PETor SPECT imaging agent and extracting data collection file dataaccording to an exemplary embodiment of the invention. The method 100 asshown in FIG. 1, may be executed or otherwise performed by one or acombination of various systems, components, and sub-systems, including acomputer implemented system. Each block shown in FIG. 1 represents oneor more processes, methods, and/or subroutines carried out in theexemplary method 100.

At block 102, a radioisotope is produced. The radioisotope (e.g., ¹⁸F or¹¹C) is typically produced using a cyclotron (e.g., GE PETtrace 700cyclotron) for PET radioisotopes or using a generator for SPECTradioisotopes (e.g., to produce the ⁹⁹Tc). The cyclotron or generatormay be located at a manufacturing site or it may be located in proximityto the scanner. Locating the cyclotron or generator on-site with the PETor SPECT scanner minimizes transportation time for the radioisotope. Itshould be appreciated that while “PET” and “SPECT” are referred toherein such examples are exemplary and the mention of one does notpreclude application to the other.

At block 104, a radiopharmaceutical is synthesized using theradioisotope. A synthesizer is used to combine the radioisotope with aradioligand. The result is a radiopharnmaceutical. The synthesizer maybe manually operated, semi-automated in operation, or fully automated.For example, the GE Healthcare FASTlab system is a fully automatedsynthesizer. The synthesizer is generally operated in a “hot cell” toshield the operator from the radioactivity of the radioisotope. Duringthe synthesis of the radiopharmaceutical, data can be collected duringthe process. The data corresponds to radiodetector or sensormeasurements at various points in the synthesis process. The data arecollected at various time intervals and may be electronically stored.The data may be output or saved in the form a data collection file. Thesynthesizer may employ a cassette which is mated thereto and containsthe various reagents and other equipment, such as syringe pumps andvials, required for the synthesis of the radiopharmaceutical. Thecassette may be removable and disposable. Cassettes may be configured tosupport the synthesis of one or more radiopharmaceuticals.

At block 106, the synthesized radiopharmaceutical is dispensed. Thedoses of the radiopharmaceutical are dispensed into collecting vials forpatient administration and for QC. A sample of the bulk synthesizedradiopharmaceutical may be dispensed directly into a QC system and/orcassette for QC testing. Systems and methods of QC testing are shown inPCT Appl. No. US 11/2011/048564 filed on Aug. 22, 2011, the contents ofwhich are incorporated herein by reference in their entirety.

At block 108, quality control checks on a radiopharmaceutical sample areperformed. There may be one or more QC checks performed. These QC checksmay be automated. The QC system may include a cassette having aplurality of components for performing the tests. The cassette may beconfigured for insertion into a QC system to carry out the QC checks.The QC system may be a stand-alone system or it may be integrated withthe synthesizer described above. Radiopharmaceutical doses are dispensedfrom the synthesizer. Sample(s) from one or more dispensed vials may beselected for QC checks. These samples may be input to the QC system.Alternatively, the QC system may be connected or coupled to thesynthesizer such that an appropriate sample may be directly output fromthe synthesizer to the QC system.

At block 110, a dose from the same production batch as the sample onwhich the QC tests were conducted is administered to a patient.

At block 112, a PET or SPECT scan is performed on the patient whoreceived the dose.

At block 114, a data collection file is produced from the synthesizer.This file, which contains data collected during the radiopharmaceuticalsynthesis, is produced. The data collection file may be formatted andcontain data as described herein. Alternatively, other formats for thefile may be used. For example, the file may be a log file such asproduced by the GE Healthcare FASTlab system as described above. The useof the term “data collection file” or “log file” herein is mean to beexemplary and non-limiting, as there are other terms that may be usedfor such a data collection file with data collected during aradiopharmaceutical process. It should be appreciated that the datacollection file may be produced at any point during the synthesisprocess.

The data collection file may be produced in hard copy format and/or maybe stored electronically. For example, the data collection file may beprinted by an output device communicatively coupled to the synthesizer,such as a printer. Alternatively, the data collection file may be outputor stored in an electronic format. For example, the synthesizer may havean electronic display or be coupled to a computer system for displayingthe data collection file in an electronic format. The data collectionfile may be electronically saved using electronic storage, eitherinternal to the synthesizer or external thereto. For example, thesynthesizer may have solid state storage, both temporary, such as randomaccess memory and/or more permanent such as flash memory or hard disktype storage.

It should also be appreciated that the synthesizer may have inputdevices to allow for user interaction with the system. These inputdevices may be communicatively coupled to the system. For example, thesynthesizer may have a QWERTY type keyboard, an alpha-numeric pad,and/or a pointing input device. Combinations of input devices arepossible. The synthesizer may be communicatively coupled to a computernetwork. For example, the synthesizer may be communicatively coupled toa local area network or similar network. Through such a networkconnection, the synthesizer may be communicatively coupled to one ormore external computers, computer systems, and/or servers. In someembodiments, the synthesizer may be communicatively coupled to theInternet. The synthesizer may be wirelessly connected to the computernetwork or may be connected by a wired interface. The synthesizer maytransmit and receive data over the computer network. For example, thedata collection file may be transmitted over the computer network toanother computer system or server. This other computer system or servermay be remotely located at a geographically separate location from thesynthesizer.

Furthermore, the synthesizer may be computer implemented such thatsynthesizer includes one or more computer processors, power sources,computer memory, and software. As stated above, the synthesizer may becommunicatively coupled to one or more external computing systems. Forexample, the synthesizer may be communicatively coupled through acomputer network, either wired or wireless or a combination of both, toan external computer system. The external computer system may providecommands to cause the synthesizer to operate as well as collect andanalyze data from the data collection file. This combination of computerhardware and software may enable to the synthesizer to automaticallyoperate and to perform certain collection of data, analysis of the data,and implementation of corrections or factors derived from the data.

At block 116, the data collection is analyzed. In accordance withexemplary embodiments, the data collection file is analyzed as describedherein. As part of the analysis, certain factors and information may begleaned from the data collection file. Using these factors andinformation, the radiopharmaceutical process may be altered, modified,and/or tuned. For example, the data analysis may determine that theprocess is not operating efficiently because a low yield is indicated.By way of non-limiting example, this may be indicative of a problem inthe reaction vessel. A fix or modification may be implemented. Such afix or modification may be manually applied by an operator or may beimplemented automatically by the synthesizer based on command issuedthrough a computer system. In some embodiments, the system may becompletely automatic and no outside intervention is needed to perform ananalysis and implement a correction or modification to the process.

FIGS. 2A and 2B depict a data collection file according to an exemplaryembodiment. For example, FIGS. 2A and 2B may depict a log file from aFASTlab system. FIG. 2A depicts a first portion 200A of the datacollection file and FIG. 2B depicts a second portion 200B of the datacollection file. The first and second portions are parts of the datacollection file: that is, FIGS. 2A and 2B may be put together side byside to form an exemplary data collection file. Alternatively, the datacollection file may be apportioned as depicted, such as being split intomultiple sections. It should be appreciated that the data collectionfile may be divided into different sections than shown. This datacollection file may represent the data collection file containing dataproduced as shown in the method 100, for example.

The data collection file has a header row 202 with labels on each of thedata columns therebelow, as shown in FIGS. 2A and 2B. Exemplary columnlabels in the header row 202 are depicted in FIGS. 2A and 2B. It shouldbe appreciated that additional or less column labels may be contained inthe data collection file. Furthermore, the data and the formatting ofthe data depicted in each of the columns is meant to be exemplary andnon-limiting. These data are meant to depict data collected during anexemplary radiopharmaceutical synthesis process for FACBC, which is usedas a non-limiting example. As shown in FIG. 2A, the data points areshown at one second intervals. Each of the data columns (labeled byheader row 202) represents a point or state in the radiopharmaceuticalprocess. Data collected from different radioactivity detectors is shown(labeled as “Activity Detector No. N,” where “N” is the detectornumber). These radioactivity detectors measure radioactivity in theirvicinity. It should be appreciated that the Activity Detectors describedherein are positioned in exemplary positioned. More or less ActivityDetectors may be used and the positioning of the Activity Detectors maybe customizable with respect to the synthesizer and the cassette.

FIG. 3 depicts a plot of data collection file data according to anexemplary embodiment. The plot 300 represents a plot of data collectionfile data, such as the data depicted in the exemplary data collectionfile of FIGS. 2A and 2B. The plot 300 has a legend 302. As can be seen,the plot 300 is a plot of the Activity Detector data for ActivityDetectors Nos. 1, 2, 4, and 5. The plot 300 may plot Activity Measured304 versus Elapsed Time 306. A detailed explanation of a data collectionfile plot is provided in FIG. 4 below. The details are equallyapplication to other data collection file plots, such as the plot 300.

FIG. 4 depicts a plot 400 with an overlay of the components of theradiopharmaceutical synthesis process. As shown by the legend 402, theplot 400 is a plot of the activity at three different detectors. Theplot 400 represents the same data as plotted in the plot 300 describedabove. The plots 300 and 400 depict the activity during theradiopharmaceutical synthesis process. Specifically, by way ofnon-limiting example, the plots 300 and 400 depict a data collectionfile obtained during the synthesis of Fluciclatide.

An exemplary radiopharmaceutical synthesis process is superimposed onthe plot 400 as shown in FIG. 4. It should be appreciated that althoughthis exemplary process is described in terms of production ofFluciclatide using ¹⁸F, the basics of the process and the components maybe used in the production of other radiopharmaceuticals with appropriatemodifications as understood in the art. The process begins with thepurification of [¹⁸F] obtained through, e.g., the nuclear reaction¹⁸O(p,n)¹⁸F by irradiation of a 95% ¹⁸-enriched water target with a 16.5MeV proton beam in a cyclotron. The radioactivity is collected on a QMAcartridge 404 where ¹⁸F is trapped; impurities are removed; and the ¹⁸Fis subsequently eluted at path 406 into a reaction vessel 408. In thereaction vessel 408, the ¹⁸F is first conditioned through a drying stepto remove solvents including residual water, thus making the ¹⁸F morereactive. Next, at 408 a, also in the reaction vessel 408, the4-trimethylammnonium benzaldehyde is labeled using the ¹⁸F, therebyreplacing the 4-trimethylammonium moiety with a ¹⁸F. The resulting4-[¹⁸F]benzaldehyde (FBA) is transferred at path 410 to an MCX cartridge412 for purification of FBA as shown at 412 a. The FBA is transferred atpath 414 back to the reaction vessel 408 and is conjugated at 408 b witha Fluciclatide precursor AH111695 to form Fluciclatide as shown at 408c. This reaction is shown in detail in Scheme I, below.

Next, using path 416, the Fluciclatide is transferred to and passedthrough the first of two SPE cartridges 418. The Fluciclatide obtainedfrom the first SPE cartridge 418 subsequently migrates to a second SPEcartridge 420 for further purification (the SPE cartridges 418 and 420may also be referred to as tC2 SPE cartridges). The Fluciclatide istransferred at 422 to a syringe 424 through which it is transferred at426 into a production collection vial (PCV) 428. Although two SPEcartridges are shown in FIG. 4, the synthesizer may have one or morethan two SPE cartridges and the SPE cartridges may be of different typesand configurations.

According to exemplary embodiments, Activity Detector No. 1 ispositioned in the vicinity of the QMA cartridge, Activity Detector No. 2is positioned in the vicinity of the Reactor Vessel, and ActivityDetector No. 5 is positioned in the vicinity of the outlet of theprocess that leads to a syringe or a production collection vial.

The elution of ¹⁸F off the QMA cartridge and into the reactor isillustrated by the sudden drop of the Activity Detector No. 1 trace andthe rapid increase of the Activity Detector No. 2 trace at section 450of the plot. The “jump” in the Activity Detector No. 2 trace afterapproximately 1000 sec (at section 452 of the plot) is caused byincreased volume in the reactor when precursor is transferred into thereactor after evaporation of solvent. This jump occurs because activityis moved closer to the detector as the volume rises inside the reactor.The only difference in height is caused by the decay of ¹⁸F. During thelabeling process, the volume remains constant and the slope of thisplateau (at section 454 of the plot) illustrates the decay of thefluoride [¹⁸F—]. The activity detector is sensitive enough to evendetect “splatter” inside the reactor when precursor is added. Thepurification of the FBA by the MCX cartridge is illustrated by the dropin the Activity Detector No. 2 trace followed by a lower plateau duringthe period the FBA is trapped inside the MCX cartridge, at section 456of the plot. In other words, there is no detector located in proximityto the MCX cartridge. The trace increases again when activity istransferred back to the reactor. It should be appreciated that theelapsed time depicted refers to the start of the sequence, not the startof the overall synthesis. After starting a sequence, a synthesizer canbe left idle for a period of time at a given step waiting for eventualdelayed fluoride. A dialog box on the synthesizer may be need to bechecked before proceeding. The start of sequence time is when this boxis checked.

After the second synthetic step the Activity Detector No. 2 trace dropswhen product was transferred out to two SPE cartridges for finalpurification as shown in section 458 of the plot. When product is elutedoff the SPE cartridge, and transferred to the production collectionvial, it passes by Activity Detector No. 5.

FIG. 5 depicts a plot showing how certain information, specificallyyield information, can be gleaned from the data collection file dataaccording to an exemplary embodiment. Plot 500 depicts a plot similar tothat of FIG. 4. The overall yield 502 is the sum of the first yield step504 and the second yield step 506. These yield values can be used toassess the performance of the overall process, as well as identifyproblem areas of the process. According to exemplary embodiments, anexemplary or “standard” process with an exemplary yield may bedetermined for the system. The resulting data collected during theexemplary process, e.g., the measurements of the Activity Detectors, isplotted. The yield can be determined as shown in FIG. 5.

This resulting plot may form an exemplary “fingerprint” for the system.Subsequent runs made using the system can then be compared to thisexemplary process. Deviations from the fingerprint can be noted throughplots of the data collection file data as described above. From analysisof the plots in this comparison, problems with the system and itsprocess may be readily identified and subsequently corrected. Accordingto exemplary embodiments, if the trace shown in FIG. 3 is taken to bethe fingerprint of a process that is optimal, a subsequent trace (e.g.,from a subsequent synthesis run or from an instrument at a differentsite) can be compared to it. If the fingerprint of the subsequent tracevaries significantly (e.g., more than 2%; more than 5%; more than 10% ormore than 15%) in any region (e.g., the region that is covered bydetectors 1, 2, 3, 4 or 5), the operator (or the synthesizerautomatically) can diagnose the step of the synthesis that is notproceeding properly. According to exemplary embodiments, variations inthe first yield step 504 and the second yield step 506 can be used toidentify where in the process a problem may be occurring, either at thelabeling step that forms [¹⁸F]FBA; the conjugation step that forms[¹⁸F]fluciclatide; or with any purification step involved in thesynthesis process.

FIG. 6 depicts a set of yield predictions according to an exemplaryembodiment. A table 600 represents data and yield predictions. The datais exemplary and non-limiting. According to exemplary embodiments, datais gathered from several synthesis runs on the same machine, as shown incolumn 602. Alternatively, or concurrently, these data can also begathered from several locations or sites. These sites may begeographically separated and each site operates a radiopharmaceuticalprocess on its synthesizer. The predicted yields, in this case fromseveral runs on the same machine, are in column 604. The reported yieldsare in column 606. The predicted yields are calculated based upon theyields obtained from a plot, such as the plot 500.

It can be recognized that the yield data gleaned from the datacollection file data agrees with the reported yield for theradiopharmaceutical. The reported yield is determined by a comparison ofthe first and second yields to the overall yield as shown in FIG. 5above. The difference between these quantities is the percentage yield.It should be appreciated that the process can have several steps andactions and this is an exemplary comparison, as additional steps andactions may need to be taken into account for determining the overallyield. It is advantageous to be able to glean overall yield data fromthe data collection file of the synthesizer because such a determinationmay mean one less QC assessment that has to be performed on the sample,post-production prior to administering any of the producedradiopharmaceutical to a patient, thus saving time and resources.

In addition to yield data one can also glean purity data from the datacollection file. One of the detectors not shown in FIGS. 4 and 5 isActivity Detector No. 4. This detector is located in the vicinity of thetwo SPE cartridges, as SPE cartridges 418 and 420 depicted in FIG. 4.While, the data from this detector is not shown in FIGS. 4 and 5, it isnevertheless collected during the synthesis run. When this data isplotted the traces shown in FIGS. 7A and 7B may be obtained. It shouldbe understood that these traces are exemplary only.

FIGS. 7A and 7B depict traces 700 and 702 of activity from ActivityDetector No. 4 for a portion of the synthesis reaction. Both figurescontain plots of multiple traces from different runs. For example, FIG.7A depicts traces from multiple runs at a particular site as indicatedby the legend 702. FIG. 7B shows three different traces obtained whilethe SPE cartridges were kept at three different temperatures, as shownby the legend 704. From these traces, it can be observed that thechanges in activity measured from the highest, or maximum, activity readby Activity Detector No. 4 and the minimum activity read by the detectorcan be correlated to the level of impurities present in theradiopharmaceutical produced in any given synthesis run (referring tothe right hand portion of the traces, shown by section 706 of thetraces). For example, in FIG. 7A, the smaller the change in activitybetween the maximum value of any given trace, such as section 710, andthe minimum value for any given trace, such as section 712, iscorrelated to high levels of impurities. In contrast, the larger thechange in activity between the maximum value of any given trace, such assection 714, and the minimum value for any given trace, such as section716, is correlated with lower levels of impurities.

FIG. 7B also depicts this behavior, in this case of the synthesis of theradiopharmaceutical anti-1-amino-3-[¹⁸F]fluorocyclobutane-1-carboxylicacid, otherwise known as FACBC. The trace 720, which depicts activity at27° C., has total impurities of 106 μg/mL. The trace 722, which depictsactivity at 30° C., has total impurities of 56 μg/mL, while the trace724, which depicts activity at 28° C., has total impurities of 79 μg/mL.The trace behavior depicts these impurity levels. From FIG. 7B, it canbe seen that the distance from the point 730 of the trace 720 to itslowest value 732, it much less than either of the similar points of thetraces 722 and 724 (such as, for example, the distance from the point734 on the trace 722 and the lowest value 736 is greater than that oftrace 720. A similar analysis may be performed for the trace 724 (withthe highest point and lowest point being labeled as 738 and 740,respectively). A specific portion of the trace at a specific time may bedesignated for the measurement of the high and low points to ensureconsistency among readings for different traces.

From the data collection file one can also glean data regarding howeffective certain processes are during the synthesis run. FIG. 8 depictsa plot 800 of a series of traces depicting a portion of runs shownactivity at Activity Detector No. 5 during the final SPE purificationstep at a particular site. The plot 800 is exemplary and non-limiting. Alegend 802 is provided. A table 804 provides a summary of the run numbervs. SPE recovery % vs. reported yield percentage.

The behavior of the traces shown in the plot 800 can be analyzed andconclusions drawn therefrom. For example, focusing on the trace and datacorresponding to run J181 (labeled by 806 in the legend 802 and thetable 804), certain behavior can be seen. For example, the large deltabetween the SPE Recovery % and the Reported Yield % is usuallyindicative of a problem in the synthesis process, specifically thelabeling step (e.g., the step yielding [¹⁸F]FBA, when theradiopharmaceutical in question is [¹⁸F]fluciclatide). In the case ofrun J181, in the synthesis of [¹⁸F]fluciclatide, such a large delta isindicative of a problem in the labeling step yielding [¹⁸F]FBA. Itshould be appreciated that in practice every step and action aremonitored and abnormal indications can be detected. For example,untypical syringe movement can be detected through the data collectionfiles. The activity detectors are capable of catching the consequence orresult of a particular step or action during the synthesis process.Hence, it can be see if the action, e.g., an atypical syringe movement,affected the outcome the production.

Data corresponding to this run can be seen in FIG. 6 at 610 also. Thedata 610 shows that the run has a low fluorination in the step of 45%(depicted in the Yield Labeling column of table 600). Based on this, thetrace 808 corresponding to this run in FIG. 8 behaves in a certainmanner. For example, the trace 808 has a higher activity than the otherruns in the latter part of FIG. 800. By noting behavior of this sort,insightful observations can be made into a particular synthesis processand what is happening at each step. This and other observations can bemade from an analysis of the data and the traces therefrom.

FIGS. 9A-C each depict an activity plots or traces from three differentproduction sites based on data collection file data. By way ofnon-limiting example, FIG. 9A represent a production run at a site inNorway, FIG. 9B represents a production run at a site in Sweden, andFIG. 9C represents a production run at a site in the UK. Each run is aFluciclatide production run using a synthesizer, which by way ofnon-limiting example are FASTlab systems here. As can be seen in eachFigure, data corresponding to Activity Detectors Nos. 1, 2, 4, and 5 areplotted for each. Legends 902, 904, and 906 on each FIG. 9A-C,respectively, provide reference to the traces for each ActivityDetector. As can be seen, each plot is similar in structure and shape tothat shown in FIGS. 3 and 4 described above, as these plots wereobtained using the same equipment and process as depicted in thoseFigures.

When comparing FIGS. 9A-C, it can be seen that there are differences inthe relative peak heights; e.g., between the readings of ActivityDetector No. 1 (QMA) and Activity Detector No. 2 (reactor) between thedifferent production sites and their specific synthesizers. In an idealcase, the readings of Activity Detectors Nos. 1 and 2 should be almostequal since the amount of activity entering reactor after elution of theQMA is supposed to be almost the same since the recovery activity fromthe QMA is >99%. The same variations are also seen between ActivityDetectors Nos. 2 and 5. The differences between Activity Detectors Nos.2 and 5 are used for the overall yield predictions (as described above).Hence, inaccuracy of these two detectors effects the accuracy of yieldprediction. In data given in FIG. 6 (which represents data correspondingto FIG. 9A), correlation between estimated and reported yields isobserved. However, when the same estimations are done on othersynthesizers, e.g., FIGS. 9B and 9C, the effect of variations betweenActivity Detectors Nos. 2 and 5 are seen. FIG. 10 includes this data.FIG. 10 depicts a data table corresponding to the plots of FIGS. 9A-C.The data 1002 labeled as “NMS” corresponds to FIG. 9A; the data 1004labeled as “UI” corresponds to FIG. 9B; and the data 1006 labeled as“TGC” corresponds to FIG. 9C. The differences in yield data may beattributed to the differences in the Activity Detector measurements.

As seen in FIG. 10, the accuracy of the yield prediction varies betweensites and particular synthesizers. In order to use the data for analysisof the synthesizer production for troubleshooting or otherinvestigations, the data from the data collection files, e.g., logfiles, (as described above) are extracted from the synthesizer andanalyzed. Plots, such as those in FIGS. 9A-C are created. However, sincethere are variations amongst synthesizers, even at the same site, thedata analysis may be not be directly comparable. Activity trending maybe a useful tool for monitoring reaction performance.

A method of correcting activity detector measurements is described. Abasic synthesizer sequence where a known amount of activity is passed invicinity of the different Activity Detectors. This is accomplished bymating a cassette with the synthesizer (as would be done if a productionrun was being made. The cassette may be specifically configured cassetteto support the required measurements or a production cassette may beused, possibly with modifications. No chemical reactions are required.The operations required are trapping and elution of the QMA cartridgewith an accurately known volume followed by movement of the eluted18F-fluoride solution around the cassette using syringe movements andgas pressure. A correlation factor for each detector can then becalculated as shown in the following example.

When activity arrives from the cyclotron, the activity is accuratelymeasured in an ion chamber. For illustration purposes, the net activitytransferred on to the synthesizer in this example is 100 GBq. In thesynthesizer, Activity Detector No. 1 reads 80 GBq, Activity Detector No.2 reads 110 GBq, and Activity Detector No. 5 reads 90 GBq. The readingsare then adjusted for decay. For simplification of the present example,the decay correction is not included. Based on the readings, thecorrelation factors for this particular synthesizer would then be:

Correlation factor for Activity Detector No. 1: 100/80=1.25

Correlation factor for Activity Detector No. 2: 100/110=0.91

Correlation factor for Activity Detector No. 5: 100/90=1.11

Data for the other detectors including any custom placed additionaldetectors can of course be obtained in the same manner and correlationfactors can be calculated. The correlation factors can then be usedduring the data analysis of the data collection file. This methodologydoes not require a modification to the synthesizer system's programming.It should be appreciated that calculation could be a part of a PETcenter set-up since the detector check is straightforward. Thisoperation could be repeated on regular basis to see if detectors need tobe calibrated. This operation can be repeated with different activitiesfor control of the radio detector linearity. This operation can becarried out across multiple sites and, by using the correlation factors,activity detector readings can be compared across these multiple sites.It should further be appreciated that additional correlation factors canbe calculated to compare data from synthesizers to other baselines orstandards.

While the foregoing description includes details and specific examples,it is to be understood that these have been included for purposes ofexplanation only, and are not to be interpreted as limitations of thepresent invention.

While the embodiments have been particularly shown and described above,it will be appreciated that variations and modifications may be effectedby a person of ordinary skill in the art without departing from thescope of the invention. Furthermore, one of ordinary skill in the artwill recognize that such processes and systems do not need to berestricted to the specific embodiments described herein. Otherembodiments, combinations of the present embodiments, and uses andadvantages of the present invention will be apparent to those skilled inthe art from consideration of the specification and practice of theinvention disclosed herein. The specification and examples should beconsidered exemplary.

What is claimed is:
 1. A method of monitoring a radiopharmaceuticalsynthesis process, comprising: generating, by at least one computerprocessor of a radiopharmaceutical synthesizer system, a set of dataincluding at least a) a first activity measurement obtained at a firsttime point in the radiopharmaceutical synthesis process by at least oneof a first radioactivity detector or a first sensor and b) a secondactivity measurement obtained at a second time point in theradiopharmaceutical synthesis process by at least one of a secondradioactivity detector or a second sensor, wherein i) the at least oneof the first radioactivity detector or the first sensor and ii) at leastone of a second radioactivity detector or a second sensor are locateddifferently in the radiopharmaceutical synthesizer system; generating,based on the set of data, a diagnostic fingerprint indicating activitymeasured with respect to time for execution of the radiopharmaceuticalsynthesis process; and outputting the diagnostic fingerprint for qualitycontrol to adjust synthesizer hardware of the radiopharmaceuticalsynthesizer system in comparison to a successful synthesis process. 2.The method of claim 1, further comprising: implementing a modificationto adjust the synthesizer hardware of the radiopharmaceuticalsynthesizer system based on a command received via a computer network.3. The method of claim 1, further comprising: performing, using aquality control system, a check of the synthesizer hardware using atleast one of the first activity measurement or the second activitymeasurement.
 4. The method of claim 1, further comprising: configuring aplurality of radiodetectors located in the radiopharmaceuticalsynthesizer system to provide the first and second activitymeasurements.
 5. The method of claim 1, wherein the set of data relatesto a yield of the radiopharmaceutical synthesis process.
 6. The methodof claim 1, wherein the set of data includes data points measured andrecorded at a predefined interval during the radiopharmaceuticalsynthesis process.
 7. The method of claim 6, wherein the predefinedinterval includes one second intervals during the radiopharmaceuticalsynthesis process.
 8. The method of claim 2, wherein the synthesizerhardware is to be adjusted using a correction factor to be automaticallydetermined based on the quality control and implemented by theradiopharmaceutical synthesizer system.
 9. The method of claim 1,wherein the radiopharmaceutical synthesizer system is configured toproduce a particular radiopharmaceutical for use in conjunction withconducting a SPECT or a PET scan.
 10. The method of claim 1, wherein theradiopharmaceutical synthesis process is a first radiopharmaceuticalsynthesis process, and the set of data is a first set of data, themethod further comprising: comparing a second set of data from a secondradiopharmaceutical synthesis process to the diagnostic fingerprint toevaluate the second radiopharmaceutical synthesis process by: processingthe first set of data and the second set of data to generate a firstextracted data and a second extracted data, respectively, whereinprocessing the first set of data further includes applying a firstcorrelation factor to the first set of data to normalize the first setof data and wherein processing the second set of data further includesapplying a second correlation factor to the second set of data tonormalize the second set of data; and determining deviation of thesecond extracted data from the first extracted data to assessperformance of the second radiopharmaceutical synthesis process; andwhen the deviation indicates a correction for the secondradiopharmaceutical synthesis process, adjusting a subsequentradiopharmaceutical synthesis process by: determining a thirdcorrelation factor based on the determined deviation of the secondextracted data from the first extracted data, the third correlationfactor forming a correction factor; and implementing the correctionfactor to adjust the subsequent radiopharmaceutical synthesis processaccording to the diagnostic fingerprint of the first radiopharmaceuticalsynthesis process.